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A Knowledge-centric Computation Architecture and the Case of Knowledge Mining

Authors:
Claus-Peter Rückemann

Keywords: Knowledge Mining and Mapping; Computation Architecture; Context Creation; Universal Decimal Classification; Knowledge-centric Computing.

Abstract:
This paper presents a new architecture framework, which is the research result of a series of practical problem solving implementations and further developments of the common knowledge base and integrated application components. The framework is considered knowledge-centric, based on the fundamental knowledge resources, which constitute the fundamental base and imply the core of key assets. Besides the further knowledge development, the knowledge-centric architecture flexibly allows implementations of computation components for many scenarios and the employment of available computation infrastructures. An important quality of the architecture framework is the intrinsic value to assign different roles for the professional tasks in creation and development cycles. These roles regards the major complements of knowledge, including factual, conceptual, and procedural components as well as documentation. This paper refers to a base excerpt of previous implementations and illustrates the framework for an advanced implementation case of knowledge mining. The main goal of this research is to outline the new knowledge-centric architecture and to provide a base for further long-term multi-disciplinary implementations and realisations.

Pages: 35 to 40

Copyright: Copyright (c) IARIA, 2019

Publication date: July 28, 2019

Published in: conference

ISSN: 2308-3484

ISBN: 978-1-61208-732-0

Location: Nice, France

Dates: from July 28, 2019 to August 2, 2019